The impact of growth history and flagellation on the adhesion of various<i>Listeria monocytogenes</i>strains to polystyrene
Bibliographic record
Abstract
The contribution of growth history and flagella to adhesion of Listeria monocytogenes was analysed. An in-frame deletion on the flagellin encoding gene (flaA) was performed in L. monocytogenes EGD-e to compare its adhesion ability with the parental strain, after cultivation at various pH values and temperatures. The pH, as well as the temperature, affected the adhesion of L. monocytogenes EGD-e. In addition, the adhesion of L. monocytogenes EGD-e was reduced in energy-depressed cells. Conversely, the physicochemical bacterial surface characteristics affected by growth history did not influence the adhesion. Adhesion variations observed among environmental and clinical strains was attributed to the flagella. The naturally aflagellated strains resulted in an adhesion capacity similar to that observed for mutants and parental strains cultivated under flagellum expression repressing conditions. However, L. monocytogenes is able to adhere to inert surfaces through a residual adhesion process without flagella. All these observations emphasize the importance to consider the food environmental factors in the risk assessment of L. monocytogenes in food industry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".